Backdoor Attacks and Countermeasures in Natural Language Processing Models: A Comprehensive Security Review. (arXiv:2309.06055v2 [cs.CR] UPDATED)

Deep Neural Networks (DNNs) have led to unprecedented progress in various
natural language processing (NLP) tasks. Owing to limited data and computation
resources, using third-party data and models has become a new paradigm for
adapting various tasks. However, research shows that it has some potential
security vulnerabilities because attackers can manipulate the training process
and data source. Such a way can set specific triggers, making the model exhibit
expected behaviors that have little inferior influence on the model's
performance for …

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